A randomized trial of mailed questionnaires versus telephone interviews: Response patterns in a survey

Data for health surveys are often collected using either mailed questionnaires, telephone interviews or a combination. Mode of data collection can affect the propensity to refuse to respond and result in different patterns of responses. The objective of this paper is to examine and quantify effects of mode of data collection in health surveys.

A stratified sample of 4,000 adults residing in Denmark was randomised to mailed questionnaires or computer-assisted telephone interviews. 45 health-related items were analyzed; four concerning behaviour and 41 concerning self assessment. Odds ratios for more positive answers and more frequent use of extreme response categories (both positive and negative) among telephone respondents compared to questionnaire respondents were estimated. Tests were Bonferroni corrected.

For the four health behaviour items there were no significant differences in the response patterns. For 32 of the 41 health self assessment items the response pattern was statistically significantly different and extreme response categories were used more frequently among telephone respondents (Median estimated odds ratio: 1.67). For a majority of these mode sensitive items (26/32), a more positive reporting was observed among telephone respondents (Median estimated odds ratio: 1.73). The overall response rate was similar among persons randomly assigned to questionnaires (58.1%) and to telephone interviews (56.2%). A differential nonresponse bias for age and gender was observed. The rate of missing responses was higher for questionnaires (0.73 – 6.00%) than for telephone interviews (0 – 0.51%). The "don't know" option was used more often by mail respondents (10 – 24%) than by telephone respondents (2 – 4%).

The mode of data collection affects the reporting of self assessed health items substantially. In epidemiological studies, the method effect may be as large as the effects under investigation. Caution is needed when comparing prevalences across surveys or when studying time trends.